Optimum solution of the CIECAM 02 yellow–blue and purple problems

Self Cite

210

195

The CIECAM02 color‐appearance model enjoys popularity in scientific research and industrial applications since it was recommended by the CIE in 2002. However, it has been found that computational failures can occur in certain cases such as during the image processing of cross‐media color reproduction applications. Some proposals have been developed to repair the CIECAM02 model. However, all the proposals developed have the same structure as the original CIECAM02 model and solve the problems concerned at the expense of losing accuracy of predicted visual data compared with the original model. In this article, the structure of the CIECAM02 model is changed and the color and luminance adaptations to the illuminant are completed in the same space rather than in two different spaces, as in the original CIECAM02 model. It has been found that the new model (named CAM16) not only overcomes the previous problems, but also the performance in predicting the visual results is as good as if not better than that of the original CIECAM02 model. Furthermore the new CAM16 model is simpler than the original CIECAM02 model. In addition, if considering only chromatic adaptation, a new transformation, CAT16, is proposed to replace the previous CAT02 transformation. Finally, the new CAM16‐UCS uniform color space is proposed to replace the previous CAM02‐UCS space. A new complete solution for color‐appearance prediction and color‐difference evaluation can now be offered.

“…We already know that the source of the problem in the CIECAM02 model is the original CAT02 matrix

M_{02}

which does not satisfy the nesting rule, while the matrices

M_{H P E}

and

M_{O P T}

solve the problem and satisfy this rule: it is important that the matrix

M_{16}

M_{16}

.…”

Section: Performance Of the Cat16 Transform The Cam16 Model And Thementioning

confidence: 99%

Ω_{M}

be the chromaticity domain of all X , Y , and Z values giving non‐negative

R

G

a n d B

response signals with the transformation defined by the matrix

boldM

(see Equation ), and similarly for

Ω_{H P E}

, then the nesting rule can be exactly stated as:

Ω_{CIE} \subseteq Ω_{M} \subseteq Ω_{HPE} .

…”

Section: Introductionmentioning

confidence: 99%

“…Recently, Li et al found that there were many matrices

boldM

that satisfied the nesting rule, and a special case was the matrix

boldM

being equal to the HPE matrix

M_{H P E}

, that is, the two adaptations may use the same HPE matrix. Furthermore, Jiang et al gave an optimum solution to the yellow‐blue and purple problems with the best matrix

boldM

, named as

M_{O P T}

, achieving the following results: (a) using the matrix

M_{O P T}

the nesting rule is satisfied; (b) predicting the visual results, the CIECAM02 model with the matrix

M_{O P T}

has better accuracy than the CIECAM02 model using any other matrix

boldM

satisfying the nesting rule. It was also found that the CIECAM02 model with any of the matrices

M_{02}

M_{C A M}

M_{H P E}

, and

M_{O P T}

has approximately the same accuracy in predicting the LUTCHI and Juan and Luo color appearance dataset .…”

Section: Introductionmentioning

confidence: 99%

“…Furthermore, Jiang et al gave an optimum solution to the yellow‐blue and purple problems with the best matrix

boldM

, named as

M_{O P T}

, achieving the following results: (a) using the matrix

M_{O P T}

the nesting rule is satisfied; (b) predicting the visual results, the CIECAM02 model with the matrix

M_{O P T}

has better accuracy than the CIECAM02 model using any other matrix

boldM

satisfying the nesting rule. It was also found that the CIECAM02 model with any of the matrices

M_{02}

M_{C A M}

M_{H P E}

, and

M_{O P T}

M_{C A M}

M_{H P E}

, and

M_{O P T}

provided worse results than the original matrix

…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Comprehensive color solutions: CAM16, CAT16, and CAM16‐UCS

Wang

et al. 2017

Self Cite

210

195

Color constancy from invariant wavelength ratios: An algorithm to simplify the chromatic adaptation model

Pridmore¹

2015

In a recent article on color constancy, the chromatic adaptation model was of a novel type comprising three components separately calculated-hue, chromaticness, and lightness. The constant hue component was a simple calculation of predicted wavelength but the other two components were less direct. This article provides an algorithm to simplify the model's calculation. Calculation is far simpler and more intuitive than conventional models using complex 3 3 3 matrix transforms with their various and contentious adaptation primaries and potential disadvantages (e.g., in brightness and color gamut). The model is shown to be at least as accurate as six other (conventional) models and does not require high math skill.

The development of the CIECAM16 and visualization of its domain and range

Gao,

Xiao,

Pointer

et al. 2024

In 2022, CIE recommend the CIECAM16 color appearance model to replace the current CIECAM02 model for color management systems. In this paper we will report on how CIECAM16 was developed, describe the differences between CIECAM16 and CIECAM02, describe the phenomena CIECAM16 can predict, and show the performance of CIECAM16 in the prediction of perceptual color attributes. We will then discuss the numerical determination of the domain and range of the CIECAM16 forward transformation. Finally, the domain and ranges in various conditions are visualized. CIECAM16 is capable of the accurate prediction of color appearance under a wide range of viewing conditions and with the domain and range problems now solved, it can be effectively applied to cross‐media color image reproduction. It can also be used to estimate the color rendering properties of light sources and for the establishment of a uniform color space for color difference evaluation.